%matplotlib inline
import yt
ds = yt.load("A2052_merged_0.3-2_match-core_tmap_bgecorr.fits",
slave_files=["A2052_core_tmap_b1_m2000_.fits"],
override_fields=[("flux","counts/s/pixel"),("projected_temperature","keV")])
yt : [WARNING ] 2014-04-25 23:44:15,156 Cannot find time yt : [INFO ] 2014-04-25 23:44:15,157 Detected these axes: RA---TAN DEC--TAN yt : [WARNING ] 2014-04-25 23:44:15,394 No length conversion provided. Assuming 1 = 1 cm. yt : [INFO ] 2014-04-25 23:44:15,409 Parameters: current_time = 0.0 yt : [INFO ] 2014-04-25 23:44:15,410 Parameters: domain_dimensions = [301 301 1] yt : [INFO ] 2014-04-25 23:44:15,411 Parameters: domain_left_edge = [ 0.5 0.5 0.5] yt : [INFO ] 2014-04-25 23:44:15,412 Parameters: domain_right_edge = [ 301.5 301.5 1.5] yt : [INFO ] 2014-04-25 23:44:15,413 Parameters: cosmological_simulation = 0.0
ds.field_list
yt : [INFO ] 2014-04-25 23:44:15,491 Adding field flux to the list of fields. yt : [INFO ] 2014-04-25 23:44:15,492 Adding field projected_temperature to the list of fields. yt : [INFO ] 2014-04-25 23:44:15,524 Loading field plugins. yt : [INFO ] 2014-04-25 23:44:15,525 Loaded angular_momentum (8 new fields) yt : [INFO ] 2014-04-25 23:44:15,525 Loaded astro (14 new fields) yt : [INFO ] 2014-04-25 23:44:15,526 Loaded cosmology (20 new fields) yt : [INFO ] 2014-04-25 23:44:15,527 Loaded fluid (56 new fields) yt : [INFO ] 2014-04-25 23:44:15,528 Loaded fluid_vector (88 new fields) yt : [INFO ] 2014-04-25 23:44:15,530 Loaded geometric (103 new fields) yt : [INFO ] 2014-04-25 23:44:15,530 Loaded local (103 new fields) yt : [INFO ] 2014-04-25 23:44:15,531 Loaded magnetic_field (109 new fields) yt : [INFO ] 2014-04-25 23:44:15,532 Loaded species (109 new fields)
[('fits', 'flux'), ('fits', 'projected_temperature')]
slc = yt.SlicePlot(ds, "z", ["flux","projected_temperature"], origin="native")
slc.set_log("flux",True)
slc.set_width(250.)
slc.show()
yt : [INFO ] 2014-04-25 23:44:15,691 xlim = 0.500000 301.500000 yt : [INFO ] 2014-04-25 23:44:15,692 ylim = 0.500000 301.500000 yt : [INFO ] 2014-04-25 23:44:15,692 Making a fixed resolution buffer of (('fits', 'flux')) 800 by 800 yt : [INFO ] 2014-04-25 23:44:15,750 Making a fixed resolution buffer of (('fits', 'projected_temperature')) 800 by 800 yt : [INFO ] 2014-04-25 23:44:15,766 xlim = 0.500000 301.500000 yt : [INFO ] 2014-04-25 23:44:15,766 ylim = 0.500000 301.500000 yt : [INFO ] 2014-04-25 23:44:15,767 Making a fixed resolution buffer of (('fits', 'flux')) 800 by 800 yt : [INFO ] 2014-04-25 23:44:15,785 Making a fixed resolution buffer of (('fits', 'projected_temperature')) 800 by 800 yt : [INFO ] 2014-04-25 23:44:15,802 Making a fixed resolution buffer of (('fits', 'flux')) 800 by 800 yt : [INFO ] 2014-04-25 23:44:15,819 Making a fixed resolution buffer of (('fits', 'projected_temperature')) 800 by 800 yt : [INFO ] 2014-04-25 23:44:16,722 Making a fixed resolution buffer of (('fits', 'flux')) 800 by 800 yt : [INFO ] 2014-04-25 23:44:16,734 Making a fixed resolution buffer of (('fits', 'projected_temperature')) 800 by 800
dd = ds.all_data()
dd["flux"].units
counts/(pixel*s)
dd["flux"].units.latex_representation()
'\\rm{counts} / \\rm{pixel} \\rm{s}'